categorical-features

Categorical-Feature-Encoding

Encoding_categorical-variables

Mostl oftenly used Encoding techniques for categorical Varibales are performed here.

FE_categorical_missing_values

In this code handling of the missing values for the categorical features from any dataset is shown.

MAchineLearning_FeatureEngineering1

In this i have performed complete feature engineering that is from handling null values, Categorical features upto performing feature scaling on our test_data and train_data.

EDA_on_HousePrice

In this repository I have performed Exploratory data analysis on the dataset famously known as House Price Prediction.

mte-plus

benchmarking various categorical encoding techniques for tabular data across 6 classification tasks and using 5 different downstream classifiers.

Residential-Energy-Appliance-Classification

Load monitoring/ load detection is one big breakthrough in tackling the problem of increasing carbon footprint. It helps to provide detailed electricity consumption information in residential households. This project is dedicated to providing a perfect estimate of the usage of the most common appliances in residential buildings.

Unsupervised_Learning_Challenge

clustering with crypto!

Supervised_Learning-Challenge

Using supervised machine learning models to determine credit worthiness

tabnet

Data Science Session: TabNet

Customer-Segmentation-using-LightGBM-Classifier

It predicts the right group of new customers by Segmentation among A, B, C, and D segments using LightGBM Classifier.

ResponseEncoding

Encode Categorical Features based on Target/Class

HR_Analysis

This is project 1 of the Udacity Data Scientist Nanodegree.

Handle-missing-values-in-Categorical-Features

Medium Post: some techniques useful to deal with missing values of Categorical Features

ML-regression-mealkit-DTC

Develop a predictive model to understand the LTV of each customer for a DTC meal-kit business.

Categorical-Feature-Encoding-Challenge-II

My solution for Kaggle competition "categorical feature encoding challenge II" with public and private score of 0.783.

target_statistic_encoding

A lightweight library for encoding categorical features in your dataset with robust k-fold target statistics in training with credibility filtering, and custom statistics.

Credit-Scoring

Data Science in the Banking Industry [Volume 1]

pyspark

Machine Learning (Pyspark-MLlib and Pyspark-Sql)

zalo-hit-song

Solution to Zalo AI Challenge 2019's Hit Song Prediction.

EDA-REGRESSION-CLASSIFICATION-WITH-BALCK-FRIDAY-DATASET

EDA-REGRESSION-CLASSIFICATION-WITH-BALCK-FRIDAY-DATASET

methods_of_artificial_intelligence

Laboratory works on Methods of Artificial Intelligence course

kaggle-redhat

Red hat dataset in kaggle competition